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Record W2046072654 · doi:10.1016/j.jom.2011.12.002

Too much of a good thing: The impact of product variety on operations and sales performance

2012· article· en· W2046072654 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueJournal of Operations Management · 2012
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicProduct Development and Customization
Canadian institutionsTellabs (Canada)
Fundersnot available
KeywordsVariety (cybernetics)BusinessProduct (mathematics)MarketingIndustrial organizationCommerceComputer scienceMathematics

Abstract

fetched live from OpenAlex

Abstract We examine the impact of product variety decisions on an operational measure – unit fill rate – and on sales performance. Results are estimated using weekly data over three years from 108 distribution centers of a major soft drink bottler. Our results show that fill rates are negatively associated with product variety at a diminishing rate. In addition, we examine the total effect of product variety on sales including both the direct effect and the indirect effect through operations performance. The total impact of product variety on sales initially is positive, although at a diminishing rate. However, beyond a certain level, increased product variety actually results in lower sales; that is, “too much of a good thing”. Thus, the findings provide a comprehensive understanding of the impact of product variety on operations and sales performance.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.685
Threshold uncertainty score0.289

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.002
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.017
GPT teacher head0.246
Teacher spread0.229 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it